ABSTRACT The Human Cancer Models Initiative (HCMI) is creating next generation cancer models that will drive the future of cancer precision medicine research. Historical cancer cell lines have been selected for their rapid proliferation on tissue culture plastic, which has made them amenable to high throughput screening such as genome-wide CRISPR/Cas9 knock-out screens. However, the historical lines have large gaps in their representation of the diversity of human cancer, and they may lack physiological relevance given their optimization for rapid proliferation. Next generation HCMI models address these concerns, but will require the development of new methods to make them useful. Specifically, standard approaches to genome editing (involving first creating Cas9- stably expressing lines and then introducing guide RNAs) will not work for slowly proliferating cells often growing in 3D. We will therefore develop all-in-one genome editing vector systems that will make it possible to bring the power of genome editing to HCMI models. In addition, standard viability read-outs of such ?drop-out? screens involve the growth of cells over many population doublings. But for slowly proliferating HCMI models, alternative readouts will be required for efficient screening. We will therefore develop short-term single cell RNA sequencing (scRNAseq) methods that will serve as surrogate read-outs for long-term viability. Given the clinical annotation associated with HCMI models, there is also enormous opportunity to expand the use of these models beyond viability measures to more complex, physiologically relevant phenotypes such as organ-specific metastatic potential. We will therefore develop methods that make it possible to determine the metastatic potential for next generation cancer models, and we will create a public resource of the metastasis map (MetMap) for at least 50 HCMI models. All data and protocols will be made publicly available without restriction, all reagents will be made available via Addgene, and all modified models made available to ATCC for distribution. Importantly, throughout the project, all cell models will be rigorously monitored for evidence of genetic and epigenetic drift. At the conclusion of the proposed project, we expect to have generated a set of tools and data that will help propel the future of cancer precision medicine based on next generation cancer models.